Answering top-K query combined keywords and structural queries on RDF graphs. (July 2017)

• Record Type: Journal Article
• Authors: Peng, Peng; Zou, Lei; Qin, Zheng
• Is Part Of: Information systems. Volume 67(2017)
• Page Start: 19
• Page End: 35
• Publication Date: 2017-07
• Subjects: SPARQL -- Keyword search -- RDF graph; Database management -- Periodicals; Electronic data processing -- Periodicals; Bases de données -- Gestion -- Périodiques; Informatique -- Périodiques; Database management; Electronic data processing; Periodicals; 005.7
• DOI: 10.1016/j.is.2017.03.002
• Languages: English
• ISSNs: 0306-4379

Abstract

Abstract: Although SPARQL has been the predominant query language over RDF (Resource Description Framework) graphs, some query intentions cannot be captured well using only SPARQL syntax. On the other hand, keyword search enjoys widespread usage because of its intuitive way of specifying information needs, but suffers from the problem of low precision. To maximize the advantages of both SPARQL and keyword search, we introduce a novel paradigm that combines them and propose a hybrid query (called a S PARQL- K eyword (SK) query) that integrates SPARQL and keyword search. To answer SK queries efficiently, we propose a novel integrated query algorithm based on a structural index. We also present a distance-based optimization technique to further improve the efficiency of SK queries evaluation. We test our method in three large real RDF graphs and the experiments demonstrate both the effectiveness and efficiency of our method.